The field of medical imaging has seen significant advances since the time X-ray images were first used to determine anatomical abnormalities. Medical imaging hardware has progressed in the form of newer machines such as medical resonance imaging (MRI) scanners, computed axial tomography (CAT) scanners, etc. Due to the large amount of image data generated by such modern medical scanners, there has been and remains a need for developing image processing techniques that can automate some or all of the processes to determine the presence of anatomical abnormalities in scanned medical images.
One useful image processing technique involves the identification and labeling of specific structures of interest. For example, spine structures are highly ordered, rigid and stable in shape, which make them useful for referencing other anatomies and pathologies. To make full use of the structural advantage of spine structures, they should be extracted and labeled individually.
Spine labeling can be useful in various medical applications. One such application is in diagnostic, therapeutic and spinal anesthesia, which typically involves locating the site for lumbar puncture by using lumbar vertebrae numbers. Spine labeling can also be useful for procedures that rely on the number of ribs for reference and registration. These procedures include, for example, the placement of a needle in the second intercostal space anteriorly during emergency relief of a tension pneumothorax. In such situation, if the patient has a cervical rib, the physician can easily be misled in placing the needle in a location that is higher than necessary in the neck. Visualization of labeled ribs can also be useful for placement of a chest tube to draw a maemothorax or emphysema. If the ribs are misread, the chest tube may be misguided into the pleural space and cause injury to the thoracic or abdominal viscera. This problem is especially prevalent in developing countries, where advanced investigative facilities (e.g., X-ray or CT) are not readily available.
A further application of spine labeling involves bone grafting procedures. Without spine labeling, locating the correct rib can be difficult if there are more than twelve or less than twelve ribs. Spine analysis and labeling may also be particularly useful in locating the kidney using the angle of T12 and L1, especially in view of the difficulty in approaching the kidney during percutaneous renal biopsy and nephrectomy. Spine labeling and analysis can further be employed in surgical procedures that rely on counting the ribs from the sternal angle. Such procedures include draining pneumothorax and emphysema from the chest, which require the location of the actual site of the apex beat and other valuable levels, as well as the pleura. Other uses of spinal column labeling include, for example, forensic and medical legal pathological identifications.
Despite the importance of spine labeling and analysis, results from automatic spine segmentation and labeling techniques are typically not accurate. Labeling becomes even more complicated in atypical cases where the vertebrae (or other spine structures) have unusual characteristics (e.g., number, width, shape, size, etc.). In addition, imperfect image acquisition processes may result in noisy or incomplete scans that compound the difficulties of ascertaining the total number and positions of the vertebrae. Therefore, labels often have to be manually validated and corrected by the radiologist to ensure accuracy. This verification process, however, is extremely time-consuming and error-prone, typically involving repeated scrolling of multiple images to check the rib connections (e.g., lumbarization, sacralization, 11 or 13 T-spine, etc.) and labels of the vertebrae.
Accordingly, there is a need for improved systems and methods to facilitate efficient inspection, labeling, and analysis of the spinal column.